{"id":"W4415707275","doi":"10.1038/s41597-025-06005-5","title":"A Video Dataset for Nearshore Wave Breaking Type Classification","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Breaking wave; Workflow; Breaking strength; Limiting; Dissipation; Frame (networking); Wave height","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009194596,0.00008463611,0.00009686762,0.0001154651,0.0004829185,0.000525937,0.0006250244,0.00004466092,0.0001995916],"category_scores_gemma":[0.0002079525,0.00006810886,0.0000199641,0.0005403454,0.000169255,0.0003788118,0.0001005582,0.00007126352,0.0001450907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003959839,"about_ca_system_score_gemma":0.000129394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001741921,"about_ca_topic_score_gemma":0.0007431113,"domain_scores_codex":[0.9987362,0.00002944488,0.0001748058,0.0006235564,0.0001696339,0.0002663836],"domain_scores_gemma":[0.9984255,0.0001079252,0.00005541765,0.001289208,0.00006242899,0.00005951088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002753555,0.00001051539,0.0006472915,0.00003925932,0.00001608668,0.000002758194,0.00004792153,0.00005582985,0.0002566902,0.0002094441,0.6886208,0.3100659],"study_design_scores_gemma":[0.00009829544,0.00001045866,0.009498361,0.0000292817,0.00002158521,0.00000374391,0.0001349348,0.3545649,0.00005163185,0.000820161,0.6346878,0.00007879754],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2136894,0.004056683,0.01707522,0.01378402,0.05500444,0.004268532,0.6394041,0.0004743374,0.05224327],"genre_scores_gemma":[0.5010696,0.00001920199,0.01608244,0.0005311158,0.0002445554,3.385891e-8,0.4758287,0.000006100587,0.006218279],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.3545091,"threshold_uncertainty_score":0.5071623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1190373431567038,"score_gpt":0.315366750120919,"score_spread":0.1963294069642153,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}